Stochastic Modelling of the Dynamics of the SARS-CoV-2 Epidemic: An Africa Perspective by Rasaki, Olawale Olanrewaju, Nafiu, Lukman Abiodun, Abdisalam, Hassan Muse, Thierno, Souleymane Barry

“…In this paper, we modelled the course of action of the SARS-CoV-2 virus in Africa and its five regions at approximately a year (as at 23/02/2021) of the pandemic via a five transitional compartments SIERD (Susceptible → Exposed→ Infected →Recovery → Dead) model. The datasets for the number of confirmed cases of the virus as well as the number of recoveries and deaths due to the virus as at 23/02/2021 were extracted from Africa Centre for Disease Control (Africa CDC). …”
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An optimization approach for improving steam production of heat recovery steam generator by Awsan Mohammed, Moath Al-Mansour, Ahmed M. Ghaithan, Adel Alshibani

“…The proposed models are effectively constructed and tested using real datasets. The findings revealed that the most parameters affecting steam production include high-pressure (HP) feed gas flow, HP feed gas pressure, and the interaction between low-pressure (LP) feed gas pressure, and HP feed gas flow. …”
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sAMDGCN: sLSTM-Attention-Based Multi-Head Dynamic Graph Convolutional Network for Traffic Flow Forecasting by Shiyuan Zhang, Yanni Ju, Weishan Kong, Hong Qu, Liwei Huang

“…To validate the effectiveness of sAMDGCN, we perform extensive experiments on four real-world traffic flow datasets. Experimental results show that our proposed sAMDGCN model outperforms the advanced baseline methods in long-term traffic flow prediction tasks, demonstrating its superior performance in capturing complex and dynamic traffic patterns.…”
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Characteristics of Water Vapor in the UTLS over the Tibetan Plateau Based on AURA/MLS Observations by Yi Sun, Quanliang Chen, Ke Gui, Fangyou Dong, Xiao Feng, Qichao Long

“…Using satellite data observed by AURA/MLS and ERA-Interim reanalysis datasets, the spatial distributions and temporal variations of WV were analyzed. …”
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Enhancing Chronic Disease Prediction in IoMT-Enabled Healthcare 5.0 Using Deep Machine Learning: Alzheimer’s Disease as a Case Study by Rabia Javed, Tahir Abbas, Tariq Shahzad, Khadija Kanwal, Sadaqat Ali Ramay, Muhammad Adnan Khan, Khmaies Ouahada

“…In order to make advanced improvement in the field of healthcare 5.0, future studies should focus on refining these models and investigating how well they work with a wider range of datasets.…”
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Combined effect of incentives and coupling in multigames in two-layer networks by Luo-Luo Jiang, Yi-Ming Li, Wen-Jing Li, Attila Szolnoki

“…Within this framework, we introduce the concept of ‘external coupling’ which connects agents across different networks as acquaintances, thereby facilitating access to shared datasets. Our results indicate that the combined positive effects of external coupling and incentive mechanism lead to optimal cooperation rates and lower Gini coefficients, demonstrating a negative correlation between cooperation and inequality. …”
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A Reproducible Analysis of Sequential Recommender Systems by Filippo Betello, Antonio Purificato, Federico Siciliano, Giovanni Trappolini, Andrea Bacciu, Nicola Tonellotto, Fabrizio Silvestri

“…We conduct extensive experiments on several benchmark datasets, comparing various SRSs implemented in our resource. …”
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A Simple Visualization Method for Three-Dimensional (3D) Network by Sangkwon Kim, Chaeyoung Lee, Jintae Park, Sungha Yoon, Yongho Choi, Junseok Kim

“…It is used to describe and interpret datasets in various fields such as social network, biological network, and metabolic regulation network. …”
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A Dynamic Analysis of the Role of the Planetary- and Synoptic-Scale in the Summer of 2010 Blocking Episodes over the European Part of Russia by Anthony R. Lupo, Igor I. Mokhov, Merseid G. Akperov, Alexander V. Chernokulsky, H. Athar

“…Using the National Centers for Atmospheric Research (NCAR), National Centers for Environmental Prediction (NCEP) reanalysis datasets, the climatological and dynamic character of blocking events for summer 2010 and a precursor May blocking event were examined. …”
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XI2S-IDS: An Explainable Intelligent 2-Stage Intrusion Detection System by Maiada M. Mahmoud, Yasser Omar Youssef, Ayman A. Abdel-Hamid

“…Experiments conducted on the UNSW-NB15 and CICIDS2017 datasets demonstrate significant improvements in detection performance, with a notable reduction in false negative rates for low-frequency attacks, while maintaining high precision, recall, and F1-scores.…”
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Unveiling microbial communities with EasyAmplicon: A user‐centric guide to perform amplicon sequencing data analysis by Salsabeel Yousuf, Hao Luo, Meiyin Zeng, Lei Chen, Tengfei Ma, Xiaofang Li, Maosheng Zheng, Xin Zhou, Liang Chen, Jiao Xi, Hongye Lu, Huiluo Cao, Xiaoya Ma, Bian Bian, Pengfan Zhang, Jiqiu Wu, Renyou Gan, Baolei Jia, Linyang Sun, Zhicheng Ju, Yunyun Gao, Waqar Afzal Malik, Chuang Ma, Hujie Lyu, Yahui Li, Huiyu Hou, Yuanping Zhou, Defeng Bai, Yao Wang, Haifei Yang, Jiani Xun, Shengda Du, Tianyuan Zhang, Xiulin Wan, Kai Peng, Shanshan Xu, Tao Wen, Tong Chen, Yong‐Xin Liu

“…However, analyzing these high‐throughput datasets often necessitates extensive bioinformatics expertize, hindering accessibility for many researchers. …”
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Fourier or Wavelet bases as counterpart self-attention in spikformer for efficient visual classification by Qingyu Wang, Qingyu Wang, Duzhen Zhang, Xinyuan Cai, Tielin Zhang, Bo Xu

“…Hence, the Fourier-or-Wavelet-based spikformer (FWformer) is proposed and verified in visual classification tasks, including both static image and event-based video datasets. The FWformer can achieve comparable or even higher accuracies (0.4%–1.5%), higher running speed (9%–51% for training and 19%–70% for inference), reduced theoretical energy consumption (20%–25%), and reduced graphic processing unit (GPU) memory usage (4%–26%), compared to the standard spikformer. …”
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Semi-Supervised Machine Learning for Fault Detection and Diagnosis of a Rooftop Unit by Mohammed G. Albayati, Jalal Faraj, Amy Thompson, Prathamesh Patil, Ravi Gorthala, Sanguthevar Rajasekaran

“…In this paper, supervised and semi-supervised machine learning (ML) approaches are applied to datasets collected from an operating system in the field to develop new FDD methods and to help building owners see the value proposition of performing proactive maintenance. …”
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Bioinformatic characterization of STING expression in hematological malignancies reveals association with prognosis and anti-tumor immunity by Xiang-mei Wen, Xiang-mei Wen, Xiang-mei Wen, Zi-jun Xu, Zi-jun Xu, Zi-jun Xu, Ji-chun Ma, Ji-chun Ma, Ji-chun Ma, Min-jie Zhang, Min-jie Zhang, Min-jie Zhang, Ye Jin, Ye Jin, Jiang Lin, Jiang Lin, Jiang Lin, Jun Qian, Jun Qian, Yuan-yuan Fang, Yuan-yuan Fang, Yuan-yuan Fang, Shu-yu Luo, Shu-yu Luo, Shu-yu Luo, Zhen-wei Mao

“…Moreover, the value of STING in predicting the efficacy of immunotherapy was validated using tumor immune dysfunction and exclusion (TIDE) biomarkers and real-world immunotherapy datasets.Results and DiscussionSTING was found to be relatively highly expressed in acute myeloid leukemia (AML) and chronic myeloid leukemia, with higher STING expression correlated with poorer prognosis in AML. …”
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Revolutionizing Management Accounting: The Role of Artificial Intelligence in Predictive Analytics, Automated Reporting, and Decision-Making by Milos Pavlovic, Cedomir Gligoric, Filip Zdravkovic, Danijela Pavlovic

“…Results: The findings reveal that AI greatly enhances predictive analytics by boosting model accuracy and swiftly processing large datasets. AI-powered automated reporting improves efficiency and minimizes errors, while AI-based decision support systems deliver real-time insights and detect complex patterns, resulting in more effective strategic decisions. …”
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Deciphering the heterogeneity and plasticity of the tumor microenvironment in liver cancer provides insights for prognosis by Yihao Sun, Yihao Sun, Guojuan Shi, Jian Yang, Chun-Zhong Zhou, Chuhan Peng, Yu-Hong Luo, Ying Pan, Rui-Qi Wang

“…In this study, we thoroughly examined the liver cancer tumor environment by analyzing data from 419,866 individual cells across nine datasets involving 99 patients. By categorizing patients into different groups based on their immune cell profiles, including immune deficiency, B cells-enriched, T cells-enriched and macrophages-enriched, we better understood how these cells change in various patient subgroups. …”
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Learning Dendritic-Neuron-Based Motion Detection for RGB Images: A Biomimetic Approach by Tianqi Chen, Yuki Todo, Zhiyu Qiu, Yuxiao Hua, Delai Qiu, Xugang Wang, Zheng Tang

“…This demonstrates the practical advantage of the AVS model in applications where large-scale annotated datasets are unavailable or expensive to curate. This AVS model not only advances biologically inspired multi-channel processing but also provides a practical framework for efficient, integrated visual processing in computational models.…”
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Learning with semantic ambiguity for unbiased scene graph generation by Shanjin Zhong, Yang Cao, Qiaosen Chen, Jie Gong

“…Our approach is evaluated on widely-used datasets, including Visual Genome and Generalized Question Answering, both with over 100,000 images, providing rich visual contexts for scene graph model evaluation. …”
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Predicting the hub interactome of COVID-19 and oral squamous cell carcinoma: uncovering ALDH-mediated Wnt/β-catenin pathway activation via salivary inflammatory proteins by Pradeep Kumar Yadalam, Deepavalli Arumuganainar, Prabhu Manickam Natarajan, Carlos M. Ardila

“…This study aims to predict the interactome of OSCC and COVID-19 based on salivary inflammatory proteins. Datasets for OSCC and COVID-19 were obtained from https://www.salivaryproteome.org/differential-expression and selected for differential gene expression analysis. …”
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Evaluating the performance of snow depth reanalysis products in the arid region of Central Asia by Liancheng Zhang, Guli∙Jiapaer, Tao Yu, Hongwu Liang, Kaixiong Lin, Tongwei Ju, Philippe De Maeyer, Tim Van de Voorde

“…Errors in the five SD reanalysis datasets in certain regions may stem from inaccuracies in precipitation and air temperature forcing data. …”
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